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In this paper we focus on the parameter estimation of dynamic load modelswith stochastic terms, in particular, load models where protection settings areuncertain, such as in aggregated air conditioning units. We show how theuncertainty in the aggregated protection characteristics can be formulated as astochastic differential equation with process noise. We cast the parameterinversion within a Bayesian parameter estimation framework, and we presentmethods to include process noise. We demonstrate the benefits of consideringstochasticity in the parameter estimation and the risks of ignoring it.

Sequential Bayesian Parameter Estimation of Stochastic Dynamic Load Models